Triple

T689182
Position Surface form Disambiguated ID Type / Status
Subject Anhui E13352 entity
Predicate containsCity P294 FINISHED
Object Wuhu E68512 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Wuhu | Statement: [Anhui, containsCity, Wuhu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wuhu
Context triple: [Anhui, containsCity, Wuhu]
  • A. Wuhu chosen
    Wuhu is a major industrial and transportation hub city in southeastern Anhui Province, eastern China, situated on the lower reaches of the Yangtze River.
  • B. Hefei
    Hefei is the capital and largest city of Anhui Province in eastern China, known as a major industrial, scientific, and educational center.
  • C. Huaian
    Huaian is a historic prefecture-level city in northern Jiangsu Province, China, known as the birthplace of Premier Zhou Enlai and for its Grand Canal heritage.
  • D. Wuxi
    Wuxi is a major industrial and cultural city in eastern China, located near Lake Tai and known for its manufacturing, canals, and historic gardens.
  • E. Zhenjiang
    Zhenjiang is a historic port city in eastern China known for its strategic location on the Yangtze River and its rich cultural and culinary heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a4933e0f98819097d22766c49b61b8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a09669e4819089753204772e1fdd completed March 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbac916188190b850b247232887a2 completed March 7, 2026, 11:54 p.m.
Created at: March 1, 2026, 7:36 p.m.